Explore the vast range of titles available.

Redis is a popular key-value store database used commonly across many enterprises. Based on the latest version of Redis 4.x, this book provides useful recipes to help you overcome any obstacle when it comes to the different tasks associated with Redis - from working with data types to administering and troubleshooting your Redis solution.

Data Warehousing in the Age of the Big Data will help you and your organization make the most of unstructured data with your existing data warehouse.As Big Data continues to revolutionize how we use data, it doesn't have to create more confusion.

You receive an e-mail.It contains an offer for a complete personal computer system.It seems like the retailer read your mind since you were exploring computers on their web site just a few hours prior.

Ethereum is a public, blockchain-based distributed computing platform featuring smart contract functionality. This book is your one-stop guide to blockchain and Ethereum smart contract development. We start by introducing you to the basics of blockchain. You'll learn about hash functions, Merkle trees, forking, mining, and much more. Then you'll learn about Ethereum and smart contracts, and we'll cover Ethereum virtual machine (EVM) in detail. Next, you'll get acquainted with DApps and DAOs and see how they work. We'll also delve into the mechanisms of advanced smart contracts, taking a practical approach.You'll also learn how to develop your own cryptocurrency from scratch in order to understand the business behind ICO. Further on, you'll get to know the key concepts of the Solidity programming language, enabling you to build decentralized blockchain-based applications. We'll also look at enterprise use cases, where you'll build a decentralized microblogging site.

Machine Learning Fundamentals provides a comprehensive overview of data science, emphasizing machine learning (ML). This book covers ML fundamentals, processes, and applications, that are used as industry standards. Both supervised and unsupervised learning ML models are discussed.Topics include data collection and feature engineering techniques as well as regression, classification, neural networks (deep learning), and clustering. Motivated by the success of ML in various fields, this book is designed for a wide audience coming from various disciplines such as engineering, IT, or business and is suitable for those getting started with ML for the first time.This text can also serve as the main or supplementary text in any introductory data science course from any discipline, offering real-world applications and tools in all areas.

In the world of data science there are myriad tools available to analyze data. This book describes some of the popular software application tools along with the processes for downloading and using them in the most optimum fashion. --

Cut warranty costs by reducing fraud with transparent processes and balanced control Warranty Fraud Management provides a clear, practical framework for reducing fraudulent warranty claims and other excess costs in warranty and service operations. Packed with actionable guidelines and detailed information, this book lays out a system of efficient warranty management that can reduce costs without upsetting the customer relationship. You'll dig into the whole spectrum of warranty fraud, from simple sloppy procedures to systematic organized crime, and get to know the fraudulent parties, the victims, as well as the objectives and methods of the fraudulent activities in different scenarios. You'll learn how to implement controls to detect and reduce fraudulent claims and decrease the overall warranty costs. The impact of fraudulent claims is plainly spelled out alongside detailed descriptions of typical symptoms and process gaps present in diverse companies. A comprehensive, multi-modal framework for robust warranty management is presented as a template for revamping your own company's strategy. Fraudulent warranty claims occupy an estimated 3-15 percent of the average company's warranty costs, which generally average between 1-4 percent of sales. Many companies are unaware of the issue or struggle to take action against the claims for fear of upsetting business partners, or because they lack tangible evidence. This book details a robust warranty control framework that institutes transparency and control over the whole warranty chain—supporting the process far beyond just fraud reduction. * Understand the different actors (customers, sales channels, service agents, warranty providers, etc.) and different forms of warranty fraud * Uncover issues in your company's warranty processes * Learn methods to detect and prevent fraudulent activities * Implement a robust system of warranty cost control Warranty fraud is a major cost-control issue for most companies, but the sensitive nature of the topic leaves most reluctant to share their experiences and divulge their strategies. Warranty Fraud Management brings warranty fraud out into the open, and provides a clear, actionable framework for cost-savings through fraud reduction.

Defines the notion of an activity model learned from sensor data and presents key algorithms that form the core of the field Activity Learning: Discovering, Recognizing and Predicting Human Behavior from Sensor Data provides an in-depth look at computational approaches to activity learning from sensor data. Each chapter is constructed to provide practical, step-by-step information on how to analyze and process sensor data. The book discusses techniques for activity learning that include the following: * Discovering activity patterns that emerge from behavior-based sensor data * Recognizing occurrences of predefined or discovered activities in real time * Predicting the occurrences of activities The techniques covered can be applied to numerous fields, including security, telecommunications, healthcare, smart grids, and home automation. An online companion site enables readers to experiment with the techniques described in the book, and to adapt or enhance the techniques for their own use. With an emphasis on computational approaches, Activity Learning: Discovering, Recognizing, and Predicting Human Behavior from Sensor Data provides graduate students and researchers with an algorithmic perspective to activity learning.

Create smart systems to extract intelligent insights for decision making. You will learn about widely used Artificial Intelligence techniques for carrying out solutions in a production-ready environment. You'll explore advanced topics such as clustering, symbolic and sub-symbolic information representation, and many more.

A hands on guide to web scraping and text mining for both beginners and experienced users of R * Introduces fundamental concepts of the main architecture of the web and databases and covers HTTP, HTML, XML, JSON, SQL. * Provides basic techniques to query web documents and data sets (XPath and regular expressions). * An extensive set of exercises are presented to guide the reader through each technique. * Explores both supervised and unsupervised techniques as well as advanced techniques such as data scraping and text management. * Case studies are featured throughout along with examples for each technique presented. * R code and solutions to exercises featured in the book are provided on a supporting website.